Loss of signal dynamic range is a problem commonly caused by strong interferers in a radio frequency (RF) environment. Typical approaches employed to address strong interferers include the use of fixed or tunable notch filters. Fixed notch filters can handle known RF interferers, but cannot adapt to new interferers. Systems employing fixed notch filters must be re-designed and modified substantially if the fixed interference environment changes. Tunable notch filters, while providing more flexibility, suffer from lack of tuning resolution. In particular, tunable notch filters tend to have a constant quality factor (Q), which means that the notch bandwidth is proportional to the RF frequency. Attempts at developing tunable notch filters with adequate Q has been an active area of research for years and continues to be a significant technical challenge. However, even if tunable notch filters could meet the desired Q requirements, they still lack flexibility in that they can only cancel a single interferer per notch. Employing multiple notches essentially implies using multiple filters.
Another solution to addressing interference is to perform interference cancellation. Spatial beamforming systems can use degrees of freedom to steer spatial notches—this is the concept, for example, behind the generalized sidelobe canceller. However, these techniques do not apply to frequency cancellation and do not apply to single channel receivers in any case. Furthermore, even spatial beamformers may be susceptible to dynamic range issues caused by strong interferers. The goal of active interference cancellation is to actively cancel the interference by developing a cancellation signal, and in order to avoid problems caused by interference such as spurious signals and signal distortion, the interference is cancelled early in the RF chain.
One solution to RF interference cancellation is to estimate the interferer via a separate channel that is not in saturation, or adaptively while in saturation. An estimate of the interference is then inverted (or phase matched 180 degrees out of phase) and added to the input. In such an architecture, interference signals may be heavily attenuated in the cancellation path so that the interferer analog to digital converter (ADC) is not saturated. An adaptive filter block (or other digital signal processing (DSP) function), may then be used to filter out all signals and noise other than the interference. The interference may then be amplified, phase inverted, and added to the RF input. Time delay may be employed to allow cancellation of non-periodic signals or non-periodic signal components. An example DSP adaptive filter may consist of an analysis filter bank followed by thresholds on each filter output with filter outputs below threshold being set to zero and filter outputs above threshold being passed, followed by a synthesis filter bank. The DSP would typically also include phase adjustments and possibly additional phase matching based on monitoring of cancellation output. Reconstruction of a signal after ADC and up conversion is subject to imperfections introduced in the up conversion process and the need to know the signal frequency and phase in order to coherently cancel.